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9.836 skills encontradas
gm-scaffold
Scaffold a new Godot project: project.godot + addons + base directories + e2e/conftest.py + initial git commit. Lifetime-once role — runs only on fresh projects. Explicit invocation only — use /gm-scaffold.
mcp-driver
Runtime debugging and live project inspection via godot-mcp. Use when headless tools cannot diagnose the problem: code compiles but runtime behavior is wrong, tests pass but the game does not work as expected, or you need to inspect live state (node tree, console output, rendering). Escalation trigger: a task has failed 2+ times through the headless path (headless-build, gdunit-driver), or the iss
headless-build
Compile-check a Godot project using headless mode. Use after writing or modifying any GDScript or C# code to verify it compiles. Triggers: after code changes, before running tests, when build errors need diagnosis. Also use this when the user says "check if it compiles", "build check", "does this parse", or after any file creation/modification that could break compilation.
godot-e2e
Write and run E2E (end-to-end) game tests using the godot-e2e framework. Python controls a live Godot game over TCP — Locator-based semantic queries, expect() auto-retry assertions, and engine log capture make failures self-diagnosing. Use this skill whenever you need to: - Test actual gameplay: player movement, collisions, scoring, scene transitions - Verify UI interactions: button clicks, label
gm-verify
Mechanical verification of the built game: headless build, unit tests, lint, static checks. Explicit invocation only — use /gm-verify.
gdunit-driver
Run gdUnit4 unit tests and parse results into structured output. Use this skill after writing or modifying code to verify correctness via unit tests, when diagnosing test failures, or when writing new test files. Triggers: "run tests", "test fails", "write a test", any gdUnit4/unit test mention. Supports both GDScript (.gd) and C# (.cs) test files.
usability-testing
Plan and run usability tests on existing or prototype designs including test design, task scripts, moderation, observation, and findings synthesis. Use this skill whenever the user wants to test usability, run a moderated test, run an unmoderated test, validate a design, find usability issues, or improve task completion. Triggers on usability test, usability testing, moderated test, unmoderated te
data-warehouse-experimentation
Running experiments out of the data warehouse instead of via dedicated experiment platforms. SQL-based assignment, exposure logging discipline, metric definitions in dbt models, statistical analysis in SQL or Python, variance reduction with CUPED, sequential testing, and the operational tradeoffs vs platforms like Statsig and Optimizely. Triggers on warehouse-native experimentation, run experiment
frontend-component-build
Build production-ready frontend components with accessible markup, sensible props, defined states, and tested behavior. Use this skill whenever the user wants to build a component from scratch, refactor an existing one, design a component API, or implement a UI element with proper states and accessibility. Triggers on build a component, create a button, create a modal, create a form input, compone
cro-optimization
Run conversion rate optimization through hypothesis-driven testing including audit, hypothesis generation, test design, statistical analysis, and rollout decisions. Use this skill whenever the user wants to optimize conversion, run A/B tests, audit a funnel, generate test hypotheses, design experiments, or analyze test results. Triggers on conversion optimization, CRO, A/B test, split test, multiv
experimentation-analytics
How to read experiment results without fooling yourself. Confidence intervals, p-values, multiple testing, sequential testing, CUPED, heterogeneous treatment effects, ratio metrics, network effects, dashboard reconciliation, and the interpretation failures that produce confidently wrong shipping decisions.
experiment-design
A discipline for designing experiments (A/B tests, multivariate, holdouts) so the results actually answer the question you asked. Hypothesis writing, sample size, duration, segment analysis, interpretation, decision-making, and the common failure modes that produce confidently wrong shipping decisions.